Sensor based recommendations

ABSTRACT

User devices are used to access various forms of electronic content. Sensors in the user device or information about environmental data associated with the device, such as weather at the locale of the user device, may be used to determine the occurrence of physical events. Recommendations such as offers for sale of extended warranties, warranty replacement, and so forth may be provided based at least in part on the physical events.

BACKGROUND

A variety of user devices, such as electronic book (“e-Book”) readerdevices, desktop computers, portable computers, smartphones, tabletcomputers, and so forth are used to access various forms of electroniccontent. Extended warranties, support agreements, protective devices,and so forth may be offered at a time of sale. However, a consumer maynot take advantage of these goods or services at that time.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a system for determining physical events associatedwith a user device and generating a recommendation based at least inpart on the physical events in accordance with an embodiment of thedisclosure.

FIG. 2 illustrates a block diagram of the user device including sensorsconfigured to provide sensor data in accordance with an embodiment ofthe disclosure.

FIG. 3 illustrates a block diagram of sensor data acquired by thesensors of the user device in accordance with an embodiment of thedisclosure.

FIG. 4 illustrates a block diagram of a server configured to generaterecommendations based at least in part on the sensor data in accordancewith an embodiment of the disclosure.

FIG. 5 illustrates a block diagram of recommendation factors which maybe used by the server when generating recommendations in accordance withan embodiment of the disclosure.

FIG. 6 is a graph illustrating data from different sensors in the userdevice and the physical events described thereby in accordance with anembodiment of the disclosure.

FIG. 7 illustrates a user interface of the user device presenting itemsrecommended based, at least in part, on the sensor data in accordancewith an embodiment of the disclosure.

FIG. 8 illustrates a scenario in which a recommendation is made based atleast in part on the sensor data in accordance with an embodiment of thedisclosure.

FIG. 9 illustrates a flow diagram of a process of presenting arecommendation based on sensor data from the user device in accordancewith an embodiment of the disclosure.

FIG. 10 illustrates a flow diagram of a process of a server providing arecommendation for one or more items in accordance with an embodiment ofthe disclosure.

Certain implementations will now be described more fully below withreference to the accompanying drawings, in which various implementationsand/or aspects are shown. However, various aspects may be implemented inmany different forms and should not be construed as limited to theimplementations set forth herein. Like numbers refer to like elementsthroughout.

DETAILED DESCRIPTION

A variety of user devices, such as electronic book (“e-Book”) readerdevices, desktop computers, portable computers, smartphones, tabletcomputers, and so forth are used to access various forms of electroniccontent. Users access this content from a variety of locations andduring activities ranging from participating in a meeting to engaging insporting activities. The portability and ubiquity of these user devicesplace them in situations in which they may be damaged or destroyed.While users may be offered items such as extended warranties, protectionplans, protective devices, and so forth during checkout, adoption ratesare traditionally low. One reason for these low adoption rates is thatmany users do not perceive they personally will have a need for theitems and the benefits they provide.

Described herein are systems and methods for using sensor data,environmental data, or a combination thereof to identify physical eventsaffecting, or which may affect, the user device. One or more items arerecommended to the user, based at least in part on these physicalevents. In some implementations, presentation of the recommendation maybe made contemporaneous to occurrence of the physical event.

Physical events include, but are not limited to, drops, impacts,exposure to moisture, exposure to extreme temperatures, accidents, andso forth. The physical events may be identified using data from one ormore sensors in or associated with the user device. The data is analyzedto determine when a physical event has occurred.

The physical events may be identified using information gathered fromother sources external to the user device. This information may beprovided by a network connection available to the user device or toanother device such as a server. For example, a server may receivelocation information about the user device and weather information viathe Internet indicating high humidity in the location of the user devicewhich is above a pre-determined threshold.

Based at least in part on the physical events, recommendations for oneor more items may be made. For example, after a device is dropped, anextended warranty service may be recommended and offered to the user, orthe presence of the device in a rainy area may produce a recommendationfor a water-resistant cover. These recommendations may be presented bythe user device, or by another device contemporaneous to the physicalevent. Continuing the example, when a child drops a user device, thechild's parent may receive the recommendation for the extended warrantyservice. Because the recommendation is contemporaneous to the event,user response to the recommendations may be improved.

Illustrative System

FIG. 1 illustrates a system 100 for determining physical eventsassociated with a user device and generating a recommendation based atleast in part on the physical events. One or more user devices 102(1),102(2), 102(3), . . . 102(D) may be used by one or more users 104(1),104(2), 104(3), . . . 104(U). As used herein, letters enclosed byparenthesis such as “(U)” indicate an integer having a value greaterthan zero. The user devices 102 may include e-Book reader devices,laptops, tablet computers, game devices, media players, and so forth.The user devices 102 are described in more detail below with regard toFIG. 2.

The user device 102 may be configured to connect to a network 106. Thiscoupling may be wired or wireless. The network 106 may include, but isnot limited to, the Internet, a private network, a virtual privatenetwork, a wireless wide area network, a cellular data network, a localarea network, a metropolitan area network, a telephone network, and soforth. The network 106 may also be coupled to a server 108 and otherdevices. The user devices 102 may exchange information with other userdevices 102 or with the server 108 via the network 106. This informationexchanged may include one or more of sensor data 110, recommendationdata 112, or environmental data 114.

As described below with regard to FIG. 2, the user device 102 maycomprise one or more sensors. These sensors may generate sensor data 110which describes one or more physical conditions associated with the userdevice 102. For example, an accelerometer may provide information aboutthe motion of the user device 102. The sensor data is described below inmore detail with regard to FIG. 3.

The server 108 may use the sensor data 110, other information aboutenvironmental data associated with the user device 102, or a combinationthereof to identify physical events which have affected or may affectthe user device 102 to generate recommendation data 112. Therecommendation data 112 may comprise one or more items such as goods orservices which may be of interest to the user 104 of the user device102. These one or more items may include extended warranties, repairservices, warranty services, user device upgrades, personal services,vehicular services, and so forth. The server 108 is described below inmore detail with regard to FIG. 4.

The recommendation data 112 or a portion thereof may be presented on theuser device 102 or another device. For example, after the user 104(1)drops the user device 102(1), an advertisement for an extended warrantymay be presented on a display.

The environmental data 114 provides information about the environment inwhich the user device 102 may be present. The environmental data 114 mayinclude meteorological information such as current and predictedweather, civil data such as crime statistics, sunrise and sunset timesfor the sun, and so forth.

In some implementations, the user device 102 may be configured toidentify the physical events and provide a previously storedrecommendation. For example, where the user device 102 is unconnected tothe network 106, the physical event of the drop may still result in thepresentation of the advertisement for the extended warranty.

FIG. 2 illustrates a block diagram 200 of a user device 102 includingsensors configured to provide sensor data. The user device 102 maycomprise one or more processors 202, one or more memories 204, one ormore displays 206, one or more input/output (“I/O”) interfaces 208, oneor more sensors 210, and one or more network interfaces 212. The userdevice 102 may include other devices not depicted.

The processor 202 may comprise one or more cores and is configured toaccess and execute at least in part instructions stored in the one ormore memories 204. The one or more memories 204 comprise one or morecomputer-readable storage media (“CRSM”). The one or more memories 204may include, but are not limited to, random access memory (“RAM”), flashRAM, magnetic media, optical media, and so forth. The one or morememories 204 may be volatile in that information is retained whileproviding power or non-volatile in that information is retained withoutproviding power.

The display 206 is configured to present visual information to the user104. The display 206 may comprise a reflective or emissive displayconfigured to present images to the user 104. An emissive display emitslight to form an image. Emissive displays include, but are not limitedto, backlit liquid crystal displays, plasma displays, cathode ray tubes,light emitting diodes, image projectors, and so forth. Reflectivedisplays use incident light to form an image. This incident light may beprovided by the sun, general illumination in the room, a reading light,and so forth. Reflective displays include, but are not limited to,electrophoretic displays, interferometric displays, cholestericdisplays, and so forth. The display 206 may be configured to presentimages in monochrome, color, or both. In some implementations, thedisplay 206 of the user device 102 may use emissive, reflective, orcombination displays with emissive and reflective elements.

The one or more I/O interfaces 208 may also be provided in the userdevice 102. These I/O interfaces 208 allow for coupling devices such askeyboards, joysticks, touch sensors, cameras, microphones, speakers,haptic output devices, external memories, and so forth to the userdevice 102.

The user device 102 may include one or more sensors 210. These sensorsmay include one or more accelerometers 210(1), microphones 210(2),hygrometers 210(3), thermometers 210(4), location devices 210(5),pressure sensors 210(6), proximity sensors 210(7), and other sensors210(S). The one or more accelerometers 210(1) are configured todetermine a change in motion of the user device 102. The accelerometers210(1) may be configured to provide magnitude or scalar information,such as an acceleration of 5 meters per second per second (m/s²), orvector information such as 5 m/s² along a particular axis of the userdevice 102. As used herein, acceleration includes changes in velocityover time. This may include linear, rotational, and other motions. Forexample, increasing the speed and decreasing the speed user device 102are accelerations.

The one or more microphones 210(2) may be configured to acquire soundinformation. For example, the sound of rain or wind may be acquired bythe microphone 210(2) and used to determine a physical event such as theuser device 102 being exposed to a rainstorm. In another example, asound of the user device 102 hitting an object or surface such as duringa fall may be acquired and used to determine that an impact may havetaken place without data from an accelerometer 210(1). Sound may also beused at least in part to identify an accident involving the user device102. This accident may involve bicycles, automobiles, trains, and soforth. For example, the sound of an airbag deploying, of metal scrapingon metal, glass breaking, and so forth may be used to determine thephysical event of an automobile accident.

The one or more hygrometers 210(3) may be used to generate sensor dataabout humidity in the environment or immersion of the user device 102.For example, the user device 102 may be designed for exposure tohumidity levels below 80% without damage. As a result, the sensor datafrom the one or more hygrometers 210(3) describing a 100% relativehumidity may be identified as a physical event for which arecommendation for a water resistant cover may be provided.

The one or more thermometers 210(4) may provide temperature dataassociated with the user device 102. These temperatures may be internalto the user device 102, such as within the chassis proximate to theprocessor 202, or external to the user device 102. For example, severalphysical events where the user device 102 has been exposed totemperatures below its design operating range may result in arecommendation for another user device designed for operating in thatenvironment.

The one or more location devices 210(5) such as global positioningsystem or other navigation or positional devices may provide informationsuch as a location of the user device 102, velocity of the user device102, direction of travel of the user device 102, and so forth. Thislocation information may be geographic location (or “geolocation”) datasuch as a particular set of coordinates on the surface of the Earth, ormay be a relative location such as “in the kitchen” or “at the office.”In one example, when the location of the user device 102 is determinedto be on a body of water such as a lake, the user 104 may receive arecommendation for a floating cover for the user device 102.

The one or more pressure sensors 210(6) may be used to providebarometric readings, altitude information, and so forth. Continuing theexample, sensor data from the pressure sensor 210(6) indicating afalling air pressure along with an increase in humidity detected by thehygrometer 210(3) may indicate the user device 102 is experiencing wetweather.

The one or more proximity sensors 210(7) may provide an indication as towhether the user device 102 is proximate to another device or surface.In some implementations, the proximity sensors 210(7) may be configuredto provide information as to whether the proximate object is the user104, or an inanimate object such as a table. For example, sensor datafrom the accelerometer 210(1) indicating a fall, combined with anindication from the proximity sensor 210(7) that the user device 102 isnot near another object, combined with readings from the hygrometer210(3) indicating immersion, may be used to determine that the physicalevent is the user device 102 being dropped into water. Determination ofthis physical event may be used, at least in part, to generate arecommendation for a warranty repair or to void at least part of anexisting warranty.

Other sensors 210(S) may be present in or associated with the userdevice 102 to provide sensor data 110. For example, the other sensors210(S) may include an ambient light sensor configured to provide data asto whether the user device 102 is in sunlight.

The one or more network interfaces 212 provide for the transfer of databetween the user device 102 and another device directly such as in apeer-to-peer fashion, via the network 106, or both. The networkinterfaces 212 may include, but are not limited to, personal areanetworks (“PANs”), wired local area networks (“LANs”), wireless localarea networks (“WLANs”), wireless wide area networks (“WWANs”), and soforth. The network interfaces 212 may utilize acoustic, radio frequency,optical, or other signals to exchange data between the user device 102and another device such as an access point, a host computer, anotheruser device 102, and the like.

The one or more memories 204 may store instructions or modules forexecution by the processor 202 to perform certain actions or functions.The following modules are included by way of illustration, and not as alimitation. Furthermore, while the modules are depicted as stored in thememory 204, in some implementations, these modules may be stored atleast in part in external memory, such as in the server 108 which isaccessible to the user device 102 via the network 106. These modules mayinclude an operating system module 214 configured to manage hardwareresources such as the I/O interfaces 208 and provide various services toapplications or modules executing on the processor 202.

The one or more memories 204 may also store a datastore 216. Thedatastore 216 may comprise one or more databases, files, linked lists,or other data structures. The datastore 216 may be configured to storeat least a portion of the sensor data 110, the recommendation data 112,or other data 218.

A sensor data module 220 is stored in the memory 204. The sensor datamodule 220 is configured to receive sensor data 110 from the one or moresensors 210. The sensor data module 220 may be configured to identifyone or more physical events based at least in part on the sensor data110. The sensor data module 220 may be configured to implement one ormore pre-determined thresholds. In some implementations, differentthresholds may be assigned to different sensors 210. Minimum thresholdsmay be set such that “noise” or sensor data 110 associated with routineactivities of the user device 102 are not designated as physical events.Maximum or damage thresholds may be established indicating conditions atwhich the user device 102 is likely to be damaged or has been damaged.For example, a minimum threshold of 3 m/s² may be set for accelerationsmeasured by the accelerometer 210(1) such that casual walking whilecarrying the user device 102 does not result in identification of aphysical event. In comparison, a maximum threshold of 50 m/s² may beidentified as a damaging physical event. The thresholds may be static ordynamically adjustable. For example, based at least in part on othersensor data 110 or environmental information, the thresholds mayincrease or decrease.

A user interface module 222 is configured to provide a user interfacewhich handles inputs from and outputs to the user 104 during operationof the user device 102. User input may include key presses, touches on atouch screen, movement of the user device 102 or a portion thereof,speech input, and so forth. User outputs may include presentation on thedisplay 206, sound from a speaker, haptic output generating a physicalsensation or the appearance of a physical sensation, and so forth. Theuser interface module 222 may be configured to provide information suchas at least a portion of the recommendation data 112 comprising one ormore items on the display 206, and accept input such as an order fromthe user 104 for the one or more recommended items.

An internet browser module 224 is configured to provide access tocontent such as web pages and so forth. For example, the internetbrowser module 224 may be configured to render at least a portion ofhyper-text markup language (“HTML”) files on the display 206. In someimplementations, the recommendation data 112 or a portion thereof may bepresented by the internet browser module 224.

A diagnostic module 226 is stored in the memory 204 and configured toperform one or more tests indicative of an operational state orcondition of at least a portion of the user device 102 and generate oneor more diagnostic results. The diagnostic module 226 may be configuredto check operation of the processor 202, the memory 204, the display206, the I/O interfaces 208, devices attached to the I/O interfaces 208,the sensors 210, the network interfaces 212, and so forth. In someimplementations, the recommendation generated by the server 108 may bedetermined based in part on the diagnostic results. For example, thediagnostic results may be used to verify the user device 102 isoperational after a physical event such as a fall and beforerecommending an extended warranty.

Other modules 228 may be present in the memory 204 as well, such asvirtual private networking modules, text-to-speech modules, speechrecognition modules, and so forth.

FIG. 3 illustrates a block diagram 300 of the sensor data 110 acquiredby the sensors of the user device 102. The sensor data 110 may beacquired and in some implementations analyzed by the sensor data module220 to identify one or more physical events. In another implementation,the sensor data 110 or a portion thereof may be provided to the server108 which determines the one or more physical events.

The sensor data 110 may include one or more of acceleration 110(1),sound 110(2), humidity 110(3), temperature 110(4), location 110(5),pressure 110(6), proximity 110(7), and other data 110(D). The sensordata 110 may be generated by the one or more accelerometers 210(1), themicrophones 210(2), the hygrometers 210(3), the thermometers 210(4), thelocation devices 210(5), the pressure sensors 210(6), the proximitysensors 210(7), and other sensors 210(S), respectively.

Different user devices 102 may have different sensors 210 available. Forexample, the user device 102(1) may have an accelerometer 210(1) whichprovides acceleration data 110(1) while another user device 102(2) mayhave a microphone 210(2) but lack the accelerometer 210(1). Thus,different user devices 102 may generate different sensor data 110.

FIG. 4 illustrates a block diagram 400 of the server 108 configured togenerate recommendation data 112 based at least in part on the sensordata 110. The server 108 may comprise one or more processors 402, one ormore memories 404, one or more displays 406, one or more input/output(“I/O”) interfaces 408, and one or more network interfaces 410. Thememory 404 may store an operating system module 412 and a datastore 414.These components are similar to those described above with regard toFIG. 2. The modules and the functions below are shown on a single serverfor illustrative purposes and not by way of limitation. It is understoodthat the modules and the functions associated therewith may be providedby, or distributed across, one or more other servers.

The datastore 414 may store at least a portion of the sensor data 110received from the user devices 102, the recommendation data 112 providedto the user devices 102, environmental data 114, user device data 416,recommendation factors 418, and other data 420.

The user device data 416 provides information about one or more userdevices 102. The user device data 416 may include information such aswhat sensors 210 are available on a particular user device 102, orderhistory associated with the user device 102, and so forth.

The environmental data 114 may provide information about the environmentin which the user device 102 may be present. The environmental data 114may include meteorological information such as current and predictedweather, civil data such as crime statistics, sunrise and sunset timesfor the sun, and so forth.

The recommendation factors 418 are considerations or rules which areutilized in the recommendation process. For example, theserecommendation factors 418 may be configured to reduce risk to an entityoffering an extended warranty service by setting limits on when theextended warranty service may be recommended and purchased by the user104 for the user device 102. In some implementations the recommendationfactors 418 may be used to void at least a portion of an existingwarranty. For example, repeated falls of the device may result invoiding coverage of the display 206 from damage. The recommendationfactors are discussed below with regard to FIG. 5.

The other data 420 may include information such as payment accountinformation for the users 104, relationships between user devices 102and the users, and so forth. For example, the other data 420 may specifythat the user 104(1) owns user devices 102(1) and 102(2), sorecommendations should be provided to the user 104(1).

The datastore 414 may also store information about one or more items422(1), 422(2), . . . , 422(N). The items 422 may describe goods orservices which may be acquired or utilized by the user 104 for the userdevice 102. These may include extended warranties, repair services,warranty services, user device upgrades, protective covers, personalservices, vehicular service, and so forth.

A user interface module 424 is stored in the memory 404. The userinterface module 424 may be configured to provide a user interface, suchas a web page, which is configured for display on the user device 102 oron another device.

A recommendation module 426 is configured to generate recommendationscomprising recommendation data 112 based at least in part on the sensordata 110. This sensor data 110, as well as the recommendation data 112or a portion thereof may be stored in the datastore 414. Therecommendations may be based at least in part on one or morerecommendation factors 418. For example, a recommendation for anextended warranty item 422 may be generated by the recommendation module426 when the user device 102 has not experienced a physical event abovea maximum threshold value and is less than ninety days old.

The recommendation factors 418 are described below in more detail withregard to FIG. 5. The recommendation module 426 may provide items 422which are associated with the physical events or environmental factorsassociated with the device.

In some implementations, the recommendation module 426 or a portion ofthe functionality thereof may be provided by the user device 102. Forexample, a recommendation module 426 stored in the memory 204 may beconfigured to provide some recommendations to the user device 102 whenthe network 106 is unavailable.

An order module 428 is configured to accept and process the orders forthe one or more items 422. For example, when the recommendation data 112presents the user 104(1) with item 422(1) for an extended warranty onthe user device 102(1), and the user 104(1) places an order for the item422(1), the order module 428 takes payment and begins fulfillment of theorder. In some implementations, the order module 428 may be provided byone or more other servers.

Other modules 430 may be present in the memory 404 as well. Thesemodules may provide functions including authorization, authentication,accounting, security, and so forth.

FIG. 5 illustrates a block diagram 500 of recommendation factors 418which may be used by the recommendation module 426 of the server 108when generating recommendation data 112. Merchants, sellers, anddesigners of the user devices 102, warranty companies, and otherinterested parties may manage their risks associated with offering items422 associated with the user devices 102. For example, a warrantyprovider may wish to have some assurance or indication that the userdevice 102 is operational before issuing an extended warranty whichincludes free replacement of the user device 102 to minimize fraud.

The recommendation factors 418 may be established for user devices 102,users 104, or combinations thereof. For example, a particular user 104with several user devices 102 that experience frequent traumaticphysical events may not be presented with recommendations for anextended warranty item 422. Thus, the availability of the items 422 maybe based at least in part on the configuration of the recommendationfactors 418.

The pricing of the items 422 may also be based at least in part on therecommendation factors 418. Continuing the example, the user 104 withthe frequent traumatic physical events may be offered the extendedwarranty item 422, but at an increased cost given a greater risk thatthe extended warranty services are likely to be used.

One or more of the following recommendation factors 418 may be used bythe recommendation module 426 to generate the recommendation data 112.An elapsed time since purchase 418(1) may be considered. For example, anextended warranty item 422(1) may only be available until ninety daysafter the purchase of the user device 102.

An elapsed time since initial activation 418(2) of the user device 102may be considered. For example, the extended warranty item 422(1) may beavailable for fourteen days after initial activation and usage of theuser device 102. This allows for purchase of the device and a period ofdisuse, such as when a gift remains unopened until the occurrence of aholiday.

A nature of the physical event 418(3) may be determined and stored. Forexample, when a device is dropped and immersed, this may be categorizedas a “severe damage event” which may preclude offering the extendedwarranty item 422(1).

Elapsed time since physical event 418(4) may be considered. For example,after a non-damaging fall significant enough to generate a physicalevent, the extended warranty item 422(1) may be offered and good foronly three days, after which it expires. Pricing of the item 422 mayalso be determined at least in part on the elapsed time since physicalevent 418(4). For example, pricing for the item 422(1) may decrease overtime to encourage the user 104 to purchase the item.

A frequency of physical events 418(5) may be considered in generatingthe recommendation. For example, the occurrence of a large number offrequent physical events 418(5) may preclude offering an extendedwarranty item 422(1), or may increase the cost of that extended warrantyitem 422(1).

The recommendation factors 418 may include a severity of physical events418(6). In some implementations, physical events may be assigned aseverity on a scale of 0 to 10, with 10 being those which result indamage or are highly likely to result in damage. The severity may bedetermined based at least in part upon a magnitude of the physicalevent, duration, and other factors. For example, subjecting the userdevice 102 to a temperature in excess of 200 degrees Fahrenheit for morethan twenty minutes may be determined to damage internal components andbe assigned a severity of 10.

Device diagnostic results 418(7) may be used at least in part togenerate the recommendation data 112. The results may indicate theoperational state or health of one or more components in the user device102. For example, device diagnostic results 418(7) indicative of apotential failure of the display 206 may be used to provide an extendedwarranty item 422(1) which omits protection coverage for the display206. In another example, results which indicate no failures are observedor anticipated may result in offering the extended warranty item 422(1).

User demographics 418(8) for users 104 associated with the user devices102 may be considered in the recommendation process. The users 104 maybe associated with the user devices 102 by purchase, use, and so forth.The user demographics 418(8) may include a home location of the user104, age of the user 104, occupation of the user 104, and so forth. Forexample, a more comprehensive extended warranty item 422(2) may beoffered to younger users.

Other recommendation factors 418(F) may also be used in generating therecommendation data 112. For example, a percentage of usage of the userdevice 102 which occurs outdoors, as determined by ambient light sensorsand location information, may be considered such that when thepercentage is above a threshold amount items 422 for outdoor use arepresented and items 422 for indoor use are omitted or listed lessprominently.

Illustrative Processes

FIG. 6 is a graph 600 illustrating data from different sensors 210 inthe user device 102 and the physical events described thereby. In thisgraph, time is indicated along a horizontal axis 602 ranging from timezero to fourteen hours. For the sake of illustration, consider that thisdescribes a trip by the user 104. At time 2 hours, the user 104 leaveshome and drives to the harbor. At time 8 hours, the user has boarded afishing boat and is fishing until time 12 hours. Finally, at time hour14, the user 104 has returned to the hotel to sleep.

A magnitude 604 of a physical event is indicated along a vertical axis.This magnitude 604 may comprise a scalar quantity such as temperature,m/s², humidity and so forth. In other implementations, the magnitude 604may be representative of the severity of the physical events 418(6). Insome implementations, vector quantities may be used.

In this graph, for ease of illustration and not by way of limitation,datapoints from sensor data 110 acquired from three different sensorsare depicted. Acceleration datapoints 606 are represented by darkenedsquares. The acceleration datapoints 606 may indicate a maximum peakacceleration during the sample interval. These accelerations may bedetermined by the accelerometers 210(1). Speed datapoints 608 areindicated with circles and represent a maximum speed of the user deviceduring the sample interval. This speed may be determined by the locationdevice 210(5), such as output from a global positioning system receiver.Humidity datapoints 610 are indicated with triangles and represent amaximum relative humidity detected by the hygrometer 210(3) in the userdevice 102.

In some implementations, the sensor data 110 may be derived at least inpart from sources other than sensors 210 within the user device 102itself. For example, in this implementation, the server 108 maydetermine the speed and acceleration based on positioning or locationdata acquired by a cellular data network to which the user device 102 iscoupled via one of the network interfaces 212. Humidity may be inferredbased on environmental data about the weather in the locations at whichthe user device 102 is determined to be.

Shown here is a minimum threshold 612. A minimum threshold may be setfor the identification of physical events, such that events having amagnitude less than the minimum threshold 612 are not deemed to bephysical events. The minimum threshold 612 may be statically ordynamically set. Use of the minimum threshold 612 may prevent triggeringa recommendation from otherwise routine activities, such as walking withthe user device 102.

A damage threshold 614 is also depicted having a magnitude greater thanthe minimum threshold 612. The damage threshold 614 may be statically ordynamically set. The damage threshold 614 may be deemed to be themagnitude for a particular physical event or combination of physicalevents which results in, or is highly likely to result in, damage to theuser device 102.

A lookback window 616 may be used by the recommendation module 426during generation of the recommendation data 112. The lookback window616 allows the recommendation module 426 to account for a pattern ofoccurrence of the physical events.

This graph 600 depicts a variation of the datapoints commensurate withexemplary use for the user device 102. The datapoints vary above andbelow the minimum threshold 612. In some implementations, the physicalevents may be identified by a concurrence of one or more physicalquantities as measured or determined by the sensor data 110 which exceedthe minimum threshold 612. For the example depicted here, and by way ofillustration only, assume that physical events are identified when allthree physical quantities being measured exceed the minimum threshold612. Shown here are three physical events 618(1), 618(2), and 618(3)depicted at times 8, 10, and 12 hours, respectively, while the user 104was fishing. During this time, the speed, acceleration, and humidityexceed the minimum threshold 612 in the same interval. Thus, theseintervals are identified as containing physical events. In comparison,at time 6 hours, while driving on a highway, the speed datapoint 608 wasquite high but the acceleration 606 and the humidity 610 datapoints werebelow the threshold.

FIG. 7 illustrates a user interface 700 of the user device 102presenting recommended items 422. As described above, the recommendationmay be based at least in part on the sensor data 110, environmental data114, or both. As mentioned above, in some implementations, therecommendation data 112 or a portion thereof may be presented by theuser device 102 as shown here. A physical event message 702 is displayedwhich provides an indication to the user 104 that a physical event hasoccurred or may occur. This physical event may be identified based atleast in part on the sensor data 110 or the environmental data 114. Forexample, based at least in part on the sensor data 110 from the one ormore accelerometers 210(1), an acceleration which has exceeded a minimumthreshold has been identified as a physical event, such as a drop onto ahard surface.

A recommended item list 704 may be presented, presenting one or moreitems 422. In this example, an extended warranty and a protective coverare the recommended items 422. A purchase control 706 may also bepresented. When activated, the corresponding item 422 may be purchase.This purchase may be processed by the order module 428 of the server108. In some implementations, the purchase may be configured to occurautomatically, such as when the user 104 has previously configured orapproved this action.

In some implementations the recommendation may comprise an action byanother party. For example, instead of or in addition to the informationpresented as shown here in FIG. 7, a service representative maycommunicate with the user 104 associated with the user device 102. Forexample, the service representative may call the user 104 at apreviously determined telephone number, or initiate a chat session onthe user device 102.

FIG. 8 illustrates a scenario 800 in which a recommendation is madebased at least in part on the sensor data 110. At 802, the user 104purchases a user device 102. At that time of purchase, the user 104 mayhave been presented with various items 422 for purchase, such asextended warranties, insurance, protective covers, and so forth.However, for some reason, the user 104 chose not to purchase the items422.

At 804, a physical event occurs to the user device 102. For example, theuser 104 may have dropped the user device 102 onto the floor. Thisphysical event may have been determined based on data from the one ormore accelerometers 210(1) reporting acceleration 210(1) which exceededthe minimum threshold 612 but was below the damage threshold 614. Asdescribed, in some implementations, this may be a physical event basedon environmental data 114, such as a rain storm.

At 806, the server 108 generates recommendation data 112 by determiningone or more recommended items 422 based at least in part on the one ormore recommendation factors 418. As described above, the recommendationfactors 418 may be based in part on the physical event. For example, therecommendation factors 418 may take into account the magnitude,frequency, severity, and so forth of the physical events which have beenidentified in the sensor data 110. In this example, an extended warrantyitem 422(1) and a protective cover 422(2) item have been recommended.

At 808, at least a portion of the one or more recommended items 422 areprovided to the user 104, or another user 104 affiliated with the userdevice 102. For example, the user interface 700 may be presented on theuser device 102. In some implementations, instead of, or in addition to,the recommended items 422, a notification may be provided to the user104 affiliated with the user device 102. For example, when the user104(1) has loaned the user device 102(1) to the user 104(2), anotification such as a short message service (“SMS”) message, emailmessage, and so forth may be provided to the user 104(1) that a physicalevent has occurred.

At 810, an order is received by the server 108 for one or morerecommended items. In this example, the user 104 may have decided topurchase both the extended warranty item 422(1) and the protective cover422(2). The order module 428 may accept and process this order.

FIG. 9 illustrates a flow diagram 900 of a process of presenting arecommendation based on sensor data from the user device. This processmay be implemented by the recommendation module 426 on the server 108,on the user device 102, or by a combination thereof.

Block 902 receives sensor data 110 from one or more sensors 210 of theuser device 102. For example, the sensor data 110 or a portion of theinformation from the one or more sensors 210 may be received by thesensor data module 220. In some implementations, the sensor data module220 may apply some processing to the input, such as filtering readingsto reduce the size of the sensor data 110. The sensor data module 220may store the sensor data 110 in the datastore 216, or may transfer, viathe network interface 212 or another I/O interface 208, at least aportion of the sensor data 110 to the server 108. As described above,the sensor data 110 may comprise information about acceleration,exposure to moisture, temperature, proximity to another object, and soforth.

Block 904 determines environmental data associated with a location ofthe user device 102. The environmental data may be determined byretrieving the environmental data 114 or other information via thenetwork interfaces. For example, weather information associated with alocation of the user device 102 may be retrieved from a weatherinformation service. The environmental data may comprise currentweather, predicted weather, past weather, or a combination thereofassociated with a location of the user device 102.

Block 906 determines the occurrence of one or more physical events whenthe sensor data 110, the environmental data 114, or both indicates theone or more physical motions exceeds a pre-determined threshold. Thesensor data 110 describes various physical characteristics associatedwith the user device 102 or the environment around it. As describedabove with regard to FIG. 6, data may indicate a particular physicalcondition or state which is deemed to be a physical event. For example,casual movements of the user device 102 in the hands of the user 104 maynot be deemed a physical event, but dropping the user device 102 to thefloor would be deemed a physical event. The identification may involvethe use of pattern matching, comparison of data from a plurality of thesensors 210, and so forth.

Block 908 performs one or more diagnostic tests or receives diagnosticdata about at least a portion of the user device 102. The one or morediagnostic tests or receipt of diagnostic data may be based at least inpart on the determination of the occurrence of one or more physicalevents. As described above, this diagnostic data may be used todetermine at least in part the operational condition of the user device102. For example, the diagnostic data from the user device 102 mayindicate when the display 206 is damaged.

In some implementations, when the physical events exceed thepre-determined damage threshold 614, the diagnostic tests may beomitted, repeated, or otherwise modified. For example, where the userdevice 102 has been subjected to a 1000 m/s² acceleration when thedamage threshold is 500 m/s², the diagnostic tests may be omitted.

Block 910, based at least in part on the diagnostic data and thephysical event, presents recommendation data 112 for one or more items422. The recommendation data 112 may be generated by the recommendationmodule 426 based on the physical events. When the diagnostic returnsdiagnostic data indicating that the user device is operational withinpre-determined limits, the one or more items 422 recommended maycomprise an extended warranty for the device. When the diagnosticreturns diagnostic data indicating that the user device is operationaloutside pre-determined limits or non-operational, the one or more items422 recommended may comprise a repair service, a warranty replacement,and so forth.

Block 912 accepts an order for at least a portion of the one or moreitems 422. For example, the user may choose to order the extendedwarranty for the device.

FIG. 10 illustrates a flow diagram 1000 of a process of the server 108providing a recommendation for one or more items 422. This process maybe implemented by the recommendation module 426 on the server 108, onthe user device 102, or by a combination thereof.

Block 1002 determines the occurrence of one or more physical eventsassociated with a user device. As described above, the occurrence of oneor more physical events associated with the user device 102 may beidentified by analyzing a portion of sensor data 110 from the userdevice 102, from the environmental data 114, or a combination thereof toidentify one or more physical events exceeding pre-determinedthresholds.

Block 1004 determines one or more recommendation factors based at leastin part on the occurrence of one or more physical events associated withthe user device 102. As described above with regard to FIG. 5, therecommendation factors 418 may comprise one or more of the elapsed timesince purchase 418(1) of the user device, the elapsed time since initialactivation 418(2) of the user device, the nature of the physical event418(3), the elapsed time since the one or more physical events 418(4),the frequency of the one or more physical events 418(5), the severity ofthe one or more physical events 418(6), and so forth.

Block 1006 generates one or more recommended items 422 based at least inpart on the one or more recommendation factors 418. These recommendeditems 422 may comprise a warranty service for the user device 102 whenthe one or more physical events associated with the user device arebelow a pre-determined damage threshold.

Block 1008 provides at least a portion of the one or more recommendeditems 422 to the user device 102 or another device for presentation tothe user 104.

Block 1010 receives an order for at least a portion of the one or morerecommended items 422. In some implementations, the order may beinitiated based at least in part on a previously specified preferenceassociated with the user device 102. For example, the user 104 at timeof purchase may choose to opt-in such that when a physical event occurs,the extended warranty item 422(1) is purchased automatically.

Returning to the identification of the occurrence of the one or morephysical events of block 1002, in some implementations, theidentification may comprise analyzing at least a portion of the sensordata 110 from the user device 102 to identify one or more physicalevents. The sensor data 110 may be generated at least in part by thesensors 210 coupled to the user device 102. For example, the microphone210(2) of the user device 102 may detect a sound of water running whichoccurs above a certain volume level. This sensor data 110 may beindicative of a physical event of rain or exposure to water.

The identification may also comprise analyzing a location of the userdevice 102 and the environmental data 114 associated with the locationto identify the one or more physical events. For example, theenvironmental data 114 retrieved via the network 106 from another servermay indicate heavy rain in the city where the user device 102 islocated. The environmental data 114 may be received from another server,data input device such as an automated weather station, and so forth.

CONCLUSION

The operations and processes described and shown above may be carriedout or performed in any suitable order as desired in variousimplementations. Additionally, in certain implementations, at least aportion of the operations may be carried out in parallel. Furthermore,in certain implementations, less than or more than the operationsdescribed may be performed.

Certain aspects of the disclosure are described above with reference toblock and flow diagrams of systems, methods, apparatuses, and/orcomputer program products according to various implementations. It willbe understood that one or more blocks of the block diagrams and flowdiagrams, and combinations of blocks in the block diagrams and the flowdiagrams, respectively, can be implemented by computer-executableprogram instructions. Likewise, some blocks of the block diagrams andflow diagrams may not necessarily need to be performed in the orderpresented, or may not necessarily need to be performed at all, accordingto some implementations.

These computer-executable program instructions may be loaded onto aspecial-purpose computer or other particular machine, a processor, orother programmable data processing apparatus to produce a particularmachine, such that the instructions that execute on the computer,processor, or other programmable data processing apparatus create meansfor implementing one or more functions specified in the flow diagramblock or blocks. These computer program instructions may also be storedin a computer-readable storage media or memory that can direct acomputer or other programmable data processing apparatus to function ina particular manner, such that the instructions stored in thecomputer-readable storage media produce an article of manufactureincluding instruction means that implement one or more functionsspecified in the flow diagram block or blocks. As an example, certainimplementations may provide for a computer program product, comprising acomputer-readable storage medium having a computer-readable program codeor program instructions implemented therein, said computer-readableprogram code adapted to be executed to implement one or more functionsspecified in the flow diagram block or blocks. The computer programinstructions may also be loaded onto a computer or other programmabledata processing apparatus to cause a series of operational elements orsteps to be performed on the computer or other programmable apparatus toproduce a computer-implemented process such that the instructions thatexecute on the computer or other programmable apparatus provide elementsor steps for implementing the functions specified in the flow diagramblock or blocks.

Accordingly, blocks of the block diagrams and flow diagrams supportcombinations of means for performing the specified functions,combinations of elements or steps for performing the specified functionsand program instruction means for performing the specified functions. Itwill also be understood that each block of the block diagrams and flowdiagrams, and combinations of blocks in the block diagrams and flowdiagrams, can be implemented by special-purpose, hardware-based computersystems that perform the specified functions, elements or steps, orcombinations of special-purpose hardware and computer instructions.

Many modifications and other implementations of the disclosure set forthherein will be apparent having the benefit of the teachings presented inthe foregoing descriptions and the associated drawings. Therefore, it isto be understood that the disclosure is not to be limited to thespecific implementations disclosed and that modifications and otherimplementations are intended to be included within the scope of theappended claims. Although specific terms are employed herein, they areused in a generic and descriptive sense only and not for purposes oflimitation.

What is claimed is:
 1. A device, comprising: an accelerometer configuredto provide acceleration data indicative of one or more physical motionsof the device; a location device configured to provide location dataindicative of a position or speed of the device; at least one memorystoring computer-executable instructions; at least one processorcommunicatively coupled to the accelerometer, the location device andthe at least one memory and configured to execute thecomputer-executable instructions to: receive the acceleration dataprovided by the accelerometer and the location data provided by thelocation device; determine occurrence of one or more physical eventswhen the acceleration data exceeds a pre-determined minimum thresholdand is below a pre-determined maximum threshold; at least partly basedon the determination of the occurrence of one or more physical events,perform a diagnostic of at least a portion of the device to generatediagnostic data; and present an advertisement for one or more itemsbased at least in part on the location data, diagnostic data, and thedetermination of the occurrence of one or more physical events.
 2. Thedevice of claim 1, wherein the acceleration data includes informationindicative of an acceleration of the device.
 3. The device of claim 1,wherein when the diagnostic returns diagnostic data indicating that oneor more components of the device are operating within pre-determinedlimits, the one or more items comprise an extended warranty for thedevice.
 4. The device of claim 1, wherein when the diagnostic returnsdiagnostic data indicating that the device is operational outsidepre-determined limits or non-operational, and the one or more itemscomprise a repair service, a warranty replacement, or both.
 5. One ormore non-transitory computer-readable media storing computer-executableinstructions that, when executed by at least one processor, configurethe at least one processor to perform operations comprising: receivingsensor data from two sensors of a user device; detecting occurrence oftwo physical events of the user device, wherein for at least onephysical event of the two physical events the sensor data from the twosensors exceeds a pre-determined minimum magnitude threshold and isbelow a pre-determined maximum magnitude threshold; and based at leastin part on the detected occurrence of the two physical events,generating a recommendation of one or more items.
 6. The one or morenon-transitory computer-readable media of claim 5, the sensor datacomprising data for two or more of acceleration, exposure to moisture,temperature, or proximity to another object.
 7. The one or morenon-transitory computer-readable media of claim 5, wherein the twophysical events comprise an automobile accident and the recommendationof one or more items comprises recommendation of personal services. 8.The one or more non-transitory computer-readable media of claim 5, theoperations further comprising determining environmental data associatedwith the user device and the generating the recommendation based atleast in part on the environmental data.
 9. The one or morenon-transitory computer-readable media of claim 8, the operationsfurther comprising retrieving the environmental data from a server via anetwork interface.
 10. The one or more non-transitory computer-readablemedia of claim 8, the environmental data comprising current weather,predicted weather, past weather, or a combination thereof associatedwith a location of the user device.
 11. The one or more non-transitorycomputer-readable media of claim 5, further comprising receivingdiagnostic data from the user device, and the generating therecommendation based at least in part on the diagnostic data.
 12. Theone or more non-transitory computer-readable media of claim 11, thediagnostic data from the user device comprising an indication that adisplay is damaged.
 13. The one or more non-transitory computer-readablemedia of claim 5, wherein the pre-determined maximum magnitude thresholdis a damage threshold at which damage to the user device is highlylikely.
 14. One or more non-transitory computer-readable media storingcomputer-executable instructions that, when executed by at least oneprocessor, configure the at least one processor to perform operationscomprising: determining occurrence of two or more physical eventsassociated with a user device; determining one or more recommendationfactors based at least in part on the occurrence of the two or morephysical events associated with the user device, wherein determining theoccurrence of the two or more physical events comprises analyzing aportion of sensor data from the user device, wherein the portion of thesensor data is in excess of one or more pre-determined thresholds ofminimum severity and is below one or more pre-determined thresholds ofmaximum severity; and generating one or more recommended items based atleast in part on the one or more recommendation factors.
 15. The one ormore non-transitory computer-readable media of claim 14, wherein thedetermining occurrence of the two or more physical events associatedwith the user device further comprises detecting a sound of water with amicrophone of the user device.
 16. The one or more non-transitorycomputer-readable media of claim 14, the one or more recommendationfactors comprising one or more of: an elapsed time since purchase of theuser device; an elapsed time since initial activation of the userdevice; an elapsed time since the two or more physical events; or anature of at least one of the two or more physical events.
 17. The oneor more non-transitory computer-readable media of claim 14, wherein thedetermining the occurrence of the two or more physical events furthercomprises analyzing a location of the user device and environmental dataassociated with the location.
 18. The one or more non-transitorycomputer-readable media of claim 14, further comprises receiving anorder for at least a portion of the one or more recommended items. 19.The one or more non-transitory computer-readable media of claim 14,wherein the one or more recommended items comprises a warranty servicefor the user device when sensor data monitored during occurrence of thetwo or more physical events does not exceed a pre-determined damagethreshold.
 20. The one or more non-transitory computer-readable media ofclaim 14, further comprising, based at least in part on a previouslyspecified preference associated with the user device, initiating anorder for at least a portion of the one or more recommended items. 21.The one or more non-transitory computer-readable media of claim 14,further comprising one or more of the following sensors coupled to theuser device and configured to generate the sensor data: anaccelerometer; a microphone; a hygrometer; a thermometer; a globalpositioning system receiver; a pressure sensor; or a proximity sensor.